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researcher

Jacob Andreas

MIT

31 papers hereh-index 5312.1k citations93 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author4
  • first author3
  • middle author14
  • last author8

Across the 29 of 31 papers where every author was matched, so the position is known.

fields
  • cs.CL18
  • cs.CV4
  • cs.LG4
  • cs.FL1
  • cs.PL1
  • cs.RO1
affiliations
  • MIT
  • Microsoft
Homepage
same name
  • Jacob Andreas — 19 papers
  • Jacob Andreas — 3 papers, h 4
  • Jacob Andreas — 3 papers
  • Jacob Andreas — 2 papers
  • Jacob Andreas — 1 paper
  • Jacob Andreas — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20122022
most citedMeasuring Compositionality in Representation Learning

24 citations · 136 across the 19 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2020★ 15 cited

Are Visual Explanations Useful? A Case Study in Model-in-the-Loop Prediction

Eric Chu, Deb Roy, Jacob Andreas

We present a randomized controlled trial for a model-in-the-loop regression task, with the goal of measuring the extent to which (1) good explanations of model predictions increase…

cs.LG2020

Compositional Explanations of Neurons

Jesse Mu, Jacob Andreas

We describe a procedure for explaining neurons in deep representations by identifying compositional logical concepts that closely approximate neuron behavior. Compared to prior wor…

cs.LG2019

A Survey of Reinforcement Learning Informed by Natural Language

Jelena Luketina, Nantas Nardelli, Gregory Farquhar +5

To be successful in real-world tasks, Reinforcement Learning (RL) needs to exploit the compositional, relational, and hierarchical structure of the world, and learn to transfer it…

cs.LG2019★ 24 cited

Measuring Compositionality in Representation Learning

Jacob Andreas

Many machine learning algorithms represent input data with vector embeddings or discrete codes. When inputs exhibit compositional structure (e.g. objects built from parts or proced…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.